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An Application of Spatial Poisson Models to Manufacturing Investment Location Analysis

Author

Listed:
  • Lambert, Dayton M.
  • McNamara, Kevin T.
  • Garrett, Megan I.

Abstract

The influence product markets, agglomeration, labor, infrastructure, and government fiscal attributes had on manufacturing investment flows in Indiana between 2000 and 2004 were estimated using Poisson regression, geographically weighted regression, and a spatial general linear model. Counties with access to urbanization economies, product markets, available labor, a high-quality workforce, and transport infrastructure were more likely to attract manufacturing investment. These effects were magnified to some extent when inter-county spatial effects were modeled. The distributional assumptions of the spatial models are different, but both methods are useful for understanding the spatial context of the factors influencing manufacturing investment flows.

Suggested Citation

  • Lambert, Dayton M. & McNamara, Kevin T. & Garrett, Megan I., 2006. "An Application of Spatial Poisson Models to Manufacturing Investment Location Analysis," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 38(1), pages 105-121, April.
  • Handle: RePEc:cup:jagaec:v:38:y:2006:i:01:p:105-121_02
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    Cited by:

    1. Cho, Seong-Hoon & Lambert, Dayton M. & Kim, Seung Gyu & Jung, Suhyun, 2009. "Extreme coefficients in Geographically Weighted Regression and their effects on mapping," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49117, Agricultural and Applied Economics Association.
    2. Lambert, Dayton M. & Brown, Jason P. & Florax, Raymond J.G.M., 2010. "A two-step estimator for a spatial lag model of counts: Theory, small sample performance and an application," Regional Science and Urban Economics, Elsevier, vol. 40(4), pages 241-252, July.
    3. Josep-Maria Arauzo-Carod & Miguel Manjón-Antolín, 2012. "(Optimal) spatial aggregation in the determinants of industrial location," Small Business Economics, Springer, vol. 39(3), pages 645-658, October.
    4. Yingcheng Li & Kai Zhu, 2017. "Spatial dependence and heterogeneity in the location processes of new high-tech firms in Nanjing, China," Papers in Regional Science, Wiley Blackwell, vol. 96(3), pages 519-535, August.
    5. Kinne, Jan & Resch, Bernd, 2017. "Analysing and predicting micro-location patterns of software firms," ZEW Discussion Papers 17-063, ZEW - Leibniz Centre for European Economic Research.
    6. Brown, Jason P. & Florax, Raymond J.G.M. & McNamara, Kevin T., 2008. "Evolution Of Investment Flows In U.S. Manufacturing: A Spatial Panel Approach," Working papers 42502, Purdue University, Department of Agricultural Economics.
    7. Josep‐Maria Arauzo‐Carod & Daniel Liviano‐Solis & Miguel Manjón‐Antolín, 2010. "Empirical Studies In Industrial Location: An Assessment Of Their Methods And Results," Journal of Regional Science, Wiley Blackwell, vol. 50(3), pages 685-711, August.
    8. Federico Pablo-Marti & Josep Maria Arauzo-Carod, 2011. "Cluster Analysis using Microgreographic data," ERSA conference papers ersa11p284, European Regional Science Association.
    9. Wu, Wenchao, 2017. "Agglomeration Economy and Input-output Linkage: Evidence from the Entry of the Agro-food Industry in China," Japanese Journal of Agricultural Economics (formerly Japanese Journal of Rural Economics), Agricultural Economics Society of Japan (AESJ), vol. 19.
    10. Jason P. Brown & Raymond J.G.M. Florax & Kevin T. McNamara, 2009. "Determinants Of Investme??T Flows In U.S. Manufacturing," Working Papers 09-10, Purdue University, College of Agriculture, Department of Agricultural Economics.
    11. Register, D. Lane & Lambert, Dayton M. & English, Burton C. & Jensen, Kimberly L. & Menard, R. Jamey & Wilcox, Michael D., 2012. "Geographical Analysis of US Green Sector Industry Concentration," 2012 Annual Meeting, February 4-7, 2012, Birmingham, Alabama 119742, Southern Agricultural Economics Association.
    12. Pablo Martí, Federico & Arauzo Carod, Josep Maria, 2010. "Spatial distribution of economic activities: an empirical approach usingself-organizing maps," Working Papers 2072/148482, Universitat Rovira i Virgili, Department of Economics.
    13. repec:rre:publsh:v:36:y:2006:i:2:p:140-62 is not listed on IDEAS
    14. repec:rre:publsh:v:39:y:2009:i:3:p:269-86 is not listed on IDEAS
    15. Jason Brown & Dayton Lambert, 2014. "Location decisions of natural gas extraction establishments: a smooth transition count model approach," Research Working Paper RWP 14-5, Federal Reserve Bank of Kansas City.
    16. Boxiong Wang, 2024. "Suppression of carbon emissions by agricultural financial investment: A study based on provincial panel data in China," Natural Resources Forum, Blackwell Publishing, vol. 48(3), pages 985-1000, August.
    17. Hikari ISHIDO, 2015. "Trade in Services and Japan's Bilateral FTAs: Empirics on their impacts," Discussion papers 15012, Research Institute of Economy, Trade and Industry (RIETI).
    18. Liviano Solís, Daniel & Arauzo Carod, Josep Maria, 2011. "Industrial Location and Space: New Insights," Working Papers 2072/152137, Universitat Rovira i Virgili, Department of Economics.
    19. Oscar Martinez Ibañez & Miguel Manjón Antolín & Josep-Maria Arauzo-Carod, 2013. "The Geographical Scope of Industrial Location Determinants: An Alternative Approach," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 104(2), pages 194-214, April.
    20. Wojan, Timothy R. & McGranahan, David A., 2007. "Ambient Returns: Creative Capital's Contribution to Local Manufacturing Competitiveness," Agricultural and Resource Economics Review, Cambridge University Press, vol. 36(1), pages 133-148, April.
    21. Maynard, Leigh J. & Dunaway, Tarrah & Garkovich, Lorraine & Davis, Alison F., "undated". "The Impact of Agriculture on Other Business Activity: A Nationwide Analysis Applied to Fayette County, Kentucky," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida 142131, Southern Agricultural Economics Association.

    More about this item

    JEL classification:

    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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